Pitchforks aside, are they just talking about SVD? From reading the article this guy seems to be one of those "My brand of STEM is best STEM" guys. It's pretty dishonest to pretend like standard ML algorithms are unique to astrophysics, but is there any badmath here per se?

Is it publish or perish? Leaving the Lottery “Restricting yourself to academic jobs just suppresses your own market value and hurts everyone else.” The question is, why to subsidize academics and their education for leaving their jobs.

Eigenvector decomposition is a fairly basic concept in linear algebra, and it had been in use in one form or another for at least 100 years before the invention of quantum mechanics. Additionally, this article makes it sound as if the application of principle component analysis outside of physics is novel, which it is not.

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killer-felPlease provide an R4 in order to get your post app7 months ago

The quote you used as the title isn't bad mathematics per se; it could just be a sensationalist description of principal component analysis. I guess it's incorrect to say that PCA or eigenvalue decomposition are concepts "from quantum mechanics".

As long as we’re talking about Marvel films that misuse the term “eigenvalue,” [there’s a scene from Spider-Man 2 ](https://youtu.be/nL8hVXSDmNM) where Peter is in class and the professor asks, “and the eigenvalue is?” and Peter answers, “0.23 electron volts.”

I disagree. It’s like saying differentiation is a concept from quantum physics. Sure, you use calculus in quantum physics but it’s not a concept from quantum physics.
You use eigenvalue decomposition for a whole bunch of things eg determining the definiteness of a matrix.

I think it's just the wording of the headline that makes it 'wrong'. If it said something like "A concept commonly used in quantum mechanics" or something, it would be more correct. Saying "From" quantum mechanics sounds like it's exclusive to QM, when it's not.

To be fair, a lot of modern spectral theory has been developed for and by people who wanted to use it for quantum theory, and a significant share of spectral theorists would consider themselves mathematical physicists, working on some part of quantum mechanics (I would know, I'm one).

Even at elite universities, fewer astrophysics PhDs go on to take postdoctoral fellowships or pursue competitive professorships. Now, more of them go straight to work in Silicon Valley. Astrophysicists, who wrangle massive amounts of data collected from high-powered telescopes that survey the sky, have long used machine learning models, which “train” computers to perform tasks based on examples. But machine learning can also be used to make predictions about customers, and around 2012, corporations started to staff up with people who knew how to deploy it.